Passive Infrared Motion Sensors Improved the Detection Accuracy of Nocturnal Agitation

Abstract Actigraphy has been used to detect agitation in persons with dementia, although this technology must be worn by participants. Another promising sensing methodology is passive infrared (PIR) motion, which provides continuous, low-cost, and unobtrusive data, and may also improve the detection of agitated periods. Using data from the MODERATE (Monitoring Dementia-Related Agitation Using Technology Evaluation) study, we compared the predictive value of detecting agitation in a male participant, who was 64 years old with Alzheimer’s disease (AD), living in a memory care unit, and monitored with actigraphy on his wrist and four PIR motion sensors within his living quarters. The participant’s medical record indicated that he experienced agitation during 17 nights over 96 consecutive days. 929,037 data points were captured for analysis. From each night, the features extracted from the actigraphy wearable included total and standard deviation of activity counts, activity counts in the most and the least active hours, and median activity counts in one hour. Features extracted from the PIR motion sensors included dwell durations in the areas around bed, sofa, front door and bathroom, and the number of transitions between these areas. Using logistic regression to predict agitated periods, comparable classification performances were achieved using these two sets of features (AUC = 0.74 for wearable and AUC = 0.71 for PIR motion sensors). When these two sets of features were combined, the classification performance showed notable improvement (AUC = 0.83). This study points to the value of utilizing PIR motion sensors for detecting dementia-related agitation.

Tooth decay and gum disease are two of the most common chronic health conditions in the United States, are reversible and preventable, and impact approximately 68% of older adults nationwide (CDC, 2021;World Health Organization, 2020). While the Affordable Care Act added provisions to health prevention services, oral health prevention coverage was only included for children, leaving many adults and older adults without coverage (Nasseh & Vujicic, 2017). The research team used a rapid review process using 17 key search term combinations to identify literature in three medical databases (PubMed, CINAHL, and Consumer Health Complete) to identify system and policy level barriers and opportunities to address oral health equity issues for older adults in the United States. 40 articles met inclusion criteria for thematic analysis. Findings revealed three barrier categories: 1) poor oral health literacy of patients and health care providers, 2) reimbursement variability contributing to access and utilization barriers, 3) workforce and scope of practice variability. In addition, four opportunity categories were identified: 1) community-based oral health programming for older adults, 2) new reimbursement models, 3) medical-dental collaborations, and 4) policy and practice act updates. The COVID-19 public health crisis has impacted the implementation of some system and policy level opportunities. However, new health care initiatives specific to Medicare in discussion at the national level provide an opportunity to make some headway on the policy updates needed to address the oral health of older Americans. Findings and implications will be shared with the audience. Objectives: Paid care provided in the home or through community organizations includes important support services for older adults with dementia such as cleaning and personal care assistance. These services could delay the transition to long-term care, but access may differ across sociodemographic groups. This study examined the relationship between paid care and transitioning out of the community among diverse older adults with dementia.

PAID CARE SERVICES AND TRANSITIONING OUT OF THE COMMUNITY AMONG DIVERSE OLDER ADULTS WITH DEMENTIA
Methods: Using data from 303 participants (29.4% Black) with probable dementia in the National Health and Aging Trends Study (2011-2019), subdistribution hazard models estimated the association between receiving paid care at baseline and the probability of transitioning out of the community over the next eight years. Covariate selection was guided by the Andersen model of healthcare utilization.
Results: Paid care was associated with lower risk of transitioning out of the community (SHR = 0.70, 95% CI [0.50, 0.98]). This effect was similar after controlling for predisposing factors and most prominent after controlling for enabling and need for services factors (SHR = 0.63, 95% CI [0.42, 0.94]) and was only evident among Whites. There were no racial differences in the use of paid care, but Black participants were less likely to transition out of the community than Whites despite evidencing greater care needs.
Discussion: Paid care services may help delay transitions out of the community. Future research should seek to explain racial differences in access to and/or preferences for homebased, community-based, and residential care. Wan-Tai Au-Yeung, Lyndsey Miller, Zachary Beattie, and Jeffrey Kaye, Oregon Health & Science University, Portland, Oregon, United States Actigraphy has been used to detect agitation in persons with dementia, although this technology must be worn by participants. Another promising sensing methodology is passive infrared (PIR) motion, which provides continuous, low-cost, and unobtrusive data, and may also improve the detection of agitated periods. Using data from the MODERATE (Monitoring Dementia-Related Agitation Using Technology Evaluation) study, we compared the predictive value of detecting agitation in a male participant, who was 64 years old with Alzheimer's disease (AD), living in a memory care unit, and monitored with actigraphy on his wrist and four PIR motion sensors within his living quarters. The participant's medical record indicated that he experienced agitation during 17 nights over 96 consecutive days. 929,037 data points were captured for analysis. From each night, the features extracted from the actigraphy wearable included total and standard deviation of activity counts, activity counts in the most and the least active hours, and median activity counts in one hour. Features extracted from the PIR motion sensors included dwell durations in the areas around bed, sofa, front door and bathroom, and the number of transitions between these areas. Using logistic regression to predict agitated periods, comparable classification performances were achieved using these two sets of features (AUC = 0.74 for wearable and AUC = 0.71 for PIR motion sensors). When these two sets of features were combined, the classification performance showed notable improvement (AUC = 0.83). This study points to the value of utilizing PIR motion sensors for detecting dementia-related agitation. As healthcare costs rise steadily and rapidly, researchers and policymakers are increasingly interested in reducing healthcare utilization costs. Growing evidence documents many factors that may influence healthcare utilization; however, less is known about how changes in candidate predictors influence subsequent healthcare utilization. Using data from 11,374 participants in the Health and Retirement Study Innovation in Aging, 2021, Vol. 5, No. S1

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GSA 2021 Annual Scientific Meeting